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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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interventions Systematic use in practice and data collection Ongoing analysis and refinement of teaching designs Theoretical and practical knowledge generation Generation of new digital and analogue tools and/or
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. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus
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statistics. This position will be placed under Research Thrust 2 which mainly involves mathematical physics. Requirements: The applicants must have documented strong qualifications in functional and spectral
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neural networks are large black boxes, we need both automatic methods to analyze such systems and human-interpretable certificates of the analysis results. We will devise automatic and sound methods
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. Responsibilities and qualifications The nature of this project suggests that you should have a strong interest in the mathematical and theoretical aspects of machine learning. A solid background in mathematics (e.g
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interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and
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in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our
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and European companies and international academic partners. The AI4OR group focuses on solving complex problems, which require high-level modelling, data analysis and management capabilities as
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. Your work will focus on developing physics-informed AI methods to enhance decision-making in design and operation of next generation thermal energy storage systems, such as latent heat TES and